Data Scientist, Graph ML

Overview

Valo Health is a human-centric, AI-enabled biotechnology company working to make new drugs for patients faster. The company’s Opal Computational Platform transforms drug discovery and development through a unique combination of real-world data, AI, human translational models and predictive chemistry. Valo is headquartered in Lexington, MA, with additional offices in New York, NY and Tel Aviv, Israel. To learn more, visit

Staff Data Scientist, Graph ML

• Lead the design, implementation and application of graph ML and network biology approaches to target discovery from RWD and multi-omic datasets.
• Prototype new approaches aimed at enhancing and improving Valo’s graph platform, seeking out new scientific opportunities to increase the team’s impact.
• Work with world-class engineers to ensure that graph methodologies, graph construction, and underlying data are robustly integrated, to develop generalizable solutions to core scientific problems.
• Apply your technical knowledge and intuition to break down large problems into solvable pieces. Time is limited; you’ll need to prioritize which problems are critical-path today from those that can wait.
• Be an agile and pro-active Data Science team member, providing regular updates on your work, and input into the work of your colleagues; championing data science best practices; participating in code, design, and analysis review.

• MS or PhD in a quantitative field with extensive experience at the intersection of machine learning and graph analytics
• Experience in healthcare, medicine, molecular biology, computational biology, or life sciences.
• Advanced knowledge of and experience with graph ML techniques such as Graph Neural Network (GNN) models applied to link prediction, node classification, and other biomedical-relevant computational tasks, as well as related explainability methods
• Experience or general knowledge of knowledge-graph building and graph databases
• Familiarity with general graph algorithms and relevant Python libraries
• Strong experience in Python and machine learning and/or deep-learning frameworks (e.g., PyTorch)
• Experience with data science best practices (data provenance, code versioning, reproducibility, git, etc), large-scale data analytics engines (e.g., Spark or Dask), and working in cloud environments (e.g., AWS)
• Strong data visualization, analytical, problem-solving, and communication skills, with demonstrated ability to condense, summarize, and synthesize results into informative and actionable presentations to experts from different fields.

• Experience with traditional drug discovery and development processes and approaches
• Domain expertise in neuroscience, immunology, and/or cardio-metabolic biology
• Knowledge of related data science domains, including statistical genetics, multi-omics & real-world evidence

Remote Salary Range
USD $200,600—$236,000

MA Salary Range
USD $170,000—$200,000

Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Valo Health currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Valo Health's good faith estimate as of the date of publication and may be modified in the future.

Note: At this time, we are only able to consider candidates who currently have permanent US work authorization without the need for immediate or future sponsorship.